nach der Bestellung gedruckt Neuware - Printed after ordering - Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms. This book provides necessary exposure of computational strategies, properties of CV and extracting the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV through illustrative explanations. The potential nature of CV in the context of contemporary Machine Learning strategies and the Big Data paradigms is demonstrated through selected applications. Overall, this book explains statistical parameters and knowledge representation models.

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Bibliographic Details

Title: Coefficient of Variation and Machine Learning Applications
Publisher: CRC Press
Publication Date: 2021
Language: English
ISBN 10: 1032084197
ISBN 13: 9781032084190
Binding: Taschenbuch
Condition: Neu
Dimensions: 216 millimeters width by 140 millimeters height by 8 millimeters depth
Weight: 199 grams

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Synopsis

Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms. This book provides necessary exposure of computational strategies, properties of CV and extracting the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV through illustrative explanations. The potential nature of CV in the context of contemporary Machine Learning strategies and the Big Data paradigms is demonstrated through selected applications. Overall, this book explains statistical parameters and knowledge representation models.

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K. Hima Bindu, Raghava Morusupalli, Nilanjan Dey, C. Raghavendra Rao

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